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Introduction

The simplest docker installation will not be introduced. Here I will talk about the problems I encountered when installing m3db stand-alone multi-instance cluster and the process of crawling.

Use

Prometheus does not support sharding for use with exporter + prometheus + grafana. If you use federate to do it, the architecture is more complex.

The advantages of m3db: it can be sliced and copied, which is much better than the influxdb solution. Can aggregate data storage, can sample the previous data aggregation compression to reduce the shortcomings of storage space m3db just open source, less information configuration operation is more troublesome. With the MySQL,Redis I came into contact with, MongoDB installation is not quite the same, but slightly similar to the previous maintenance of the NDIR system why not use other solutions: timescaleDB relies on PG database, installation and maintenance is very different from the MySQL I am familiar with. The InfluxDB sharding function charges other niche or does not support data read and write architecture at the same time.

The architecture diagram on the official m3db website is used here

The difference between m3db's seedNode and other data storage nodes is that its built-in ETCD service etcd service is used to store the metadata of the entire cluster, which is similar to the zookeeper function of NDIR, or it can also run coordinator alone, which is equivalent to the entrance of the entire cluster, similar to the role of NDIR's IndexDispatcher, similar to the role of MongoDB's mongos to install the architecture.

Meta data

First of all, let's download etcd and then execute it. Here we will not use clusters for the time being.

Nohup. / etcd & > / dev/null & data node

The configuration file of the first node is attached here. I will point out the points that need to be noted in the form of comments below.

Coordinator: listenAddress: type: "config" value: "0.0.0.0value 7201" # Interactive port local: namespaces:-namespace: default # Table for data storage type: unaggregated # data type retention: 48h # data save time metrics: # coordinator's own metric scope: prefix: "coordinator" prometheus: handlerPath: / metrics listenAddress: 0.0.0.0 extended 7203 # until https://github.com/m3db/m3/issues/682 is resolved sanitization: prometheus samplingRate: 1.0 extended: none tagOptions: # Configuration setting for generating metric IDs from tags. IdScheme: quoted # this must be db: logging: level: info metrics: prometheus: handlerPath: / metrics sanitization: prometheus samplingRate: 1.0 extended: detailed hostID: # measured here, it can actually be understood as nodeID resolver: config # stand-alone multiple instances, which must be set to config Read from the file that the Id config: # config section of the value: node1 # instance is configured with the etcd-related service: env: default_env zone: embedded service: m3db # service name. You can follow the service in consul to understand cacheDir: / data1/m3db/cache etcdClusters:-zone: embedded endpoints:-127.0.0.1 zone 2379 listenAddress: 0.0.0.0 zone 9000 clusterListenAddress: 0.0.0.0 cacheDir 9001 httpNodeListenAddress: 0.0.0.0 data1/m3db/cache etcdClusters 9002 httpClusterListenAddress: 0.0.0.0 cacheDir 9003 debugListenAddress: 0.0.0. 0majority 9004 client: writeConsistencyLevel: majority # write consistency level readConsistencyLevel: unstrict_majority gcPercentage: 100writeNewSeriesAsync: true writeNewSeriesLimitPerSecond: 1048576 writeNewSeriesBackoffDuration: 2ms bootstrap: bootstrappers: # launch sequence-filesystem-commitlog-peers-uninitialized_topology fs: numProcessorsPerCPU: 0.125 cache: series: Policy: lru postingsList: size: 262144 commitlog: flushMaxBytes: 524288 flushEvery: 1s blockSize: 10m queue: calculationType: fixed size: 2097152 fs: filePathPrefix: / data1/m3db # m3dbnode data directory

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